arXiv Machine Learning By Justin Tahmassebpur, Asadullah Bhuiyan, Hyejin Kim, Omri Lesser

Learning from almost nothing: How neural networks survive heavy input corruption

Read the original on arXiv Machine Learning →

arXiv:2606. 11319v1 Announce Type: new Abstract: Learning from imperfect data is a central theme in machine learning, connecting practical questions of robustness to fundamental questions of learnability.

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arXiv Machine Learning
Jun 25

Learning with Monotone Adversarial Corruptions

arXiv:2601. 02193v2 Announce Type: replace Abstract: We study the extent to which standard machine learning algorithms rely on exchangeability and independence of data by introducing a monotone adversarial corruption model.

By Kasper Green Larsen, Chirag Pabbaraju, Abhishek Shetty